ScholarGate
Assistente

Comparar métodos

Examine os métodos selecionados lado a lado; as linhas que diferem ficam destacadas.

Weighted PageRank×Centralidade de Grau Ponderado×
ÁreaAnálise de redesAnálise de redes
FamíliaMachine learningMachine learning
Ano de origem20042004
Autor originalXing, W. & Ghorbani, A.Barrat, A.; Barthélemy, M.; Pastor-Satorras, R.; Vespignani, A.
TipoCentrality measure / ranking algorithmCentrality measure for weighted networks
Fonte seminalXing, W., & Ghorbani, A. (2004). Weighted PageRank algorithm. Proceedings of the Second Annual Conference on Communication Networks and Services Research (CNSR '04), pp. 305–314. IEEE. DOI ↗Barrat, A., Barthélemy, M., Pastor-Satorras, R., & Vespignani, A. (2004). The architecture of complex weighted networks. Proceedings of the National Academy of Sciences, 101(11), 3747–3752. DOI ↗
Outros nomesWPR, weighted page rank, edge-weighted PageRank, strength-based PageRanknode strength, strength centrality, weighted node degree, WDC
Relacionados66
ResumoWeighted PageRank extends the classic PageRank algorithm to networks where edges carry different strengths or frequencies, distributing importance proportionally to both incoming and outgoing edge weights rather than treating all links equally. This makes it substantially more informative than binary PageRank in any network where connection strength matters.Weighted degree centrality — also called node strength — extends the classic degree centrality measure to networks whose edges carry numeric weights. Instead of simply counting a node's connections, it sums the weights of all edges incident to that node, capturing both the volume and the intensity of a node's ties in a single, interpretable score.
ScholarGateConjunto de dados
  1. v1
  2. 2 Fontes
  3. PUBLISHED
  1. v1
  2. 2 Fontes
  3. PUBLISHED

Ir para a pesquisa Baixar slides

ScholarGateComparar métodos: Weighted PageRank · Weighted Degree Centrality. Recuperado em 2026-06-19 de https://scholargate.app/pt/compare